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Permeability Determination of Tertiary Reservoir/Ajeel Oil Field
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This paper discusses the method for determining the permeability values of Tertiary Reservoir in Ajeel field (Jeribe, dhiban, Euphrates) units and this study is very important to determine the permeability values that it is needed to detect the economic value of oil in Tertiary Formation. This study based on core data from nine wells and log data from twelve wells. The wells are AJ-1, AJ-4, AJ-6, AJ-7, AJ-10, AJ-12, AJ-13, AJ-14, AJ-15, AJ-22, AJ-25, and AJ-54, but we have chosen three wells (AJ4, AJ6, and AJ10) to study in this paper. Three methods are used for this work and this study indicates that one of the best way of obtaining permeability is the Neural network method because the values of permeability obtained being much closer to the values of K-core than the other methods. From this study we obtained many values of permeability for all depths from top to bottom for three wells in Ajeel Field as explained by figures below.

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Publication Date
Mon Jan 01 2018
Journal Name
Al–bahith Al–a'alami
The Interactive Relationship between the Formation Elements and their Implications in the Structure of the Television Image
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The image of television dominates the cognitive and artistic motivations. It is the formulation of ideas and visions along with its documentary ability. It is the main element in television work as it is a story that is narrated in pictures. Therefore, attention to image building is a major point of gravity in the work structure as a whole. On the image is the element carrying all aesthetic and expressive values of news and information directly to the hints that work to stimulate and stir the imagination of the recipient to evoke mental images added to the visual images to deepen the meanings.
All visual arts carry elements and components that follow in a particular pattern to give special meanings and specific connotations. However,

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Microstructure properties of lead silicate glasses
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In the present work, lead silicate glasses have been prepared with
different amount of lead oxide content. Structure properties such as
X-ray diffraction, AFM, and FTIR analyses have been done. The
exceeding of PbO content more than 25wt% revealed a decreasing in
density. The X- ray revealed that the strongest peak related to
Hexagonal silica dioxide and the other crystal phases formed were
related to silica oxide (SiO2) and lead oxide (PbO). Growth and
decayed phases in X-ray have been observed with changing lead
oxide content. Homogeneous surface was obtained using AFM
analyzer with an average diameter around 100 nm. Infrared spectrum
is characterized by the presence of large absorption band between
120

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
BEARING CAPACITY OF SHALLOW FOOTINGS RESTING ON DUNE SAND
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As a result of the growth of economic, demographic and building activities in Iraq, that necessitates carrying out geotechnical investigations for the dune sand to study behavior of footings resting on these soils. To determine these properties and to assess the suitability of these materials for resting shallow foundation on it, an extensive laboratory testing program was carried out. Chemical tests were carried out to evaluate any possible effects of the mineralogical composition of the soil on behavior of foundation rested on dune sands.
Collapse tests were also conducted to trace any collapse potential. Loading tests were carried out for optimum water content and different shapes of footing. Loading test recommends manufacturing o

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Sun Jan 27 2019
Journal Name
Civil Engineering Journal
Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques
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Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated.  For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers propos

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Heat Production Rate and Radiation Hazard Indices from Radioactive Elements in Different Types of Natural Water in Nineveh Governorate, Iraq.
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The current study sheds light on the measurement and estimation of the radioactivity of radionuclides (238U, 226Ra, 232Th, and 40k) in natural waters of different regions of Nineveh Governorate in Iraq.15 samples were collected from different sources of natural waters, where gamma-ray spectroscopy was used using NaI)TI) sodium iodide detector to determine the concentration of radioactivity in the samples. According to the results, the radioactivity concentration in the tested water sample were ​​ranged from 0.36 ± 0.04-1.57 ± 0.09with an average value of 0.69 ± 0.06 Bq/l for 238U, and 2.9 ± 0.02-0.88 ± 0.03 with an average value of 0.65 ± 0.03 Bq/l for 226Ra Bq/l

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